Orthogonal frequency division multiplexing (OFDM) is a promising candidate for next generation elastic optical networks due to its inherent ability to support multiple users, its capability to adapt to channel frequency response and its dispersion tolerance. One of the important operations of OFDM reception is frame synchronization.
FIGS. 2A and 2B depict the problem OFDM reception faces. OFDM relies on modulating a large number of low bandwidth subcarriers (SCs) with data using an Inverse Fast Fourier Transform (IFFT) operation at the transmitter. The receiver uses the Fast Fourier Transform (FFT) operation to demodulate the data. OFDM data is transmitted as a series of IFFT frames—each IFFT frame consisting of data from one IFFT operation. FIGS. 2A and 2B show a sequence of IFFT frames that arrive at a receiver. Each frame includes symbols 1-N. At the receiver, it is necessary that only the data from one IFFT frame be used as input to the corresponding FFT operation. This ideal situation is shown in FIG. 2A. Practically however, there is a random temporal offset between the received IFFT frames and their expected position. This offset is depicted in FIG. 2B. In optical fiber telecommunication systems, this random temporal offset is a result of the thermal expansion and contraction of the fiber over its entire length. This results in data from one IFFT frame being part of the computation of the FFT of the subsequent IFFT frame which causes errors in the demodulated data after FFT. Hence, frame synchronization in OFDM is an important problem.
Several methods have been proposed and demonstrated to solve the frame synchronization problem. A first group of methods is based on transmitting a predefined pattern (also called training symbols or a training sequence) and determining the temporal offset by calculating the correlation between the training symbols using iterative temporal sliding. Some particular implementations of this method require a large number of samples per training symbol (˜512) and are not suitable for fiber optic OFDM communication where the requirement for Gb/s bit rates and the availability of GSa/s sampling rates do not allow for a large number of samples per symbol. Other implementations of this method rely on cross-correlating the received predefined pattern with a stored version of the predefined pattern at the receiver.
Another group of methods that have been proposed are frequency domain auto-correlation techniques. The disadvantages of this group of methods include: (a) the need for hardware multipliers to calculate correlation, this calls for more complex digital hardware; (b) iteratively calculating the temporal offset is time consuming. A maximum-likelihood (ML) based method that uses the cyclic prefix has been proposed, but this method requires hardware multipliers to calculate the ML estimate. Another method relies on transmitting the training symbols using differential-binary phase shift keying (D-BPSK) and demodulating the training symbols at the receiver using a D-BPSK demodulator and then comparing the training symbols to each other to determine the temporal offset. Here, the use of D-BPSK allows the synchronization process to be robust against the inherent random phase variations between the received signal and the carrier/local oscillator which corrupts the training symbols in the time domain. However, this also complicates the synchronization hardware due to the need for a D-BPSK demodulator. A virtual subcarrier based method also has been proposed, but this method requires hardware multipliers and is therefore more complex synchronization circuitry.